Imaging algorithms such as image enhancement, edge detection, auto-focus, and print quality control perform better if intrinsic image noise level is known. For instance, image enhancement can be more aggressive for lower noise levels.
An estimate of the noise level should be accurate. An incorrect noise estimate can lead to poor performance. For example, an incorrect noise estimate can result in overly aggressive denoising and, consequently, a blurrier image.